Project Summary Chemotherapy has made remarkable advances in the treatment of solid malignancies which cure millions of patients from breast cancer. However, the adverse effects of cardiotoxicity mediated by dose-dependent chemotherapeutic agents (such as anthracyclines) limit the efficacy of these therapies, causing left-ventricular (LV) dysfunction in the form of cardiomyopathies and even heart failure. Emerging evidence now suggest that early, myocardial strain-based, subclinical detection of cardiotoxicity may facilitate timely interventions in treatment management and therefore slow the progress of LV dysfunction and lower the incidence of heart failure. Recent clinical studies also show that the strain-based approach to detecting subclinical cardiotoxicity is superior to detections based on measuring differentials in LV ejection fraction (LVEF). The primary objective of this study is to create a highly automated, diagnostic application with an intuitive user-interface for computation of MRI-based myocardial contractile metrics in the LV in general, and to specifically use it in this study towards predicting the onset of subclinical cardiotoxicity in breast cancer patients. A parallel and equally important goal will involve demonstrating that regional contractile metrics (Lagrangian radial, circumferential and longitudinal normal strains, circumferential-radial and circumferential-longitudinal shear strains as well as twist and torsion) can predict cardiotoxicity prior to LVEF. Among the above mentioned 3D contractile metrics monitored, there will be an emphasis on our main hypothesis that torsion, which parameterizes the base-to-apex twisting motion of myofibers, is pivotal for indicating myocardial dysfunction. The source of data for these metrics will be the cardiac motion (displacements) recorded with the phase encoding MRI sequence of navigator-gated, spiral cine DENSE. Ultimately, the originality of this study will lie in our ability to fully automate the contractility measurement process including computations of 3D LV boundaries using a combination of image quantization and phase-unwrapping the DENSE data, in addition to the pointwise computation of the contractile metrics in a 3D myocardial grid of the patient?s LV using the DENSE displacements. The surveillance in each patient will be conducted at baseline (initiation of chemotherapy) and during regular follow-up investigations to determine the role that regional strain-based contractile metrics may have in detecting subclinical cardiotoxicity prior to LVEF. If established, the proof of concept for this early detection will be provided with intra-parametric and inter-parametric analysis of variance models, within and between the regional contractile metrics and LVEF and their correlations to clinical data conducted after two follow-up investigations performed on the enrolled chemotherapy patients. The ultimate goal is that this novel, contractility-based surveillance tool can provide cardio- oncologists with the direct ability to diagnose subclinical cardiotoxicity induced by chemotherapeutic agents and hence, the opportunity to intervene with cardio-protective therapy towards better treatment management.